Iris Image Specular Quality Artifact Evaluation for Biometric Recognition

Image quality assessment plays an important role in the performance of biometric systems. Data quality assessment is a key issue, in order to broaden the applicability of iris biometrics to unconstrained imaging conditions. Having empirically observed the published strategies to assess iris image quality; In this paper, we propose quality factor after assessing the prominent factors of iris like Dilation, Light variation, Occlusion and Specular reflection by their scores. Mainly Concentrating on Specular quality artifact. These factors once evaluated are then used to get quality score for a given iris image from a database. As far as possible we have ensured that this paper will follow a common protocol in deciding those features. Not only in finding the feature from one database but can be implemented and quality score can be assessed for all possible freely available databases. Initial work has been carried out from the database created by our own set up (HUWITZ HS 5000).The comparison is also done with existing databases and algorithm. This in turn will act as a benchmark in increasing the efficiency of further processing.